Jack Dunn - Reclaiming Common Sense

June Record Weekly Wages Largely Ignored

The June Jobs Report caught some people off-guard. The Current Employment Statistics (CES) worker data showed a huge spike in non-seasonally adjusted (NSA)workers. The Current Population Survey (CPS) data, NSA, recorded a huge spike in full-time jobs, a significant drop in part-time jobs, and a massive spike in U3 unemployed workers.  The unemployment rate edged higher as more people re-entered the job market. The CPS survey respondents were basically answering that they were looking for work and unable to find it. So far this column has published the following articles:

Not all jobs are created equally. We saw a huge spike in full-time jobs this month. We saw wages surge in sectors where employment had been trailing in recovery. President Trump is seeing job growth not seen since Bill Clinton, and it is in full-time job growth.  Some people are hanging on the seasonally adjusted wage data. What is the big picture, non-seasonally adjusted,  story on Wages and Earnings?

The Average June Hourly Wage for all Sectors set records. We have a record level or Current Employment Statistics (CES) workers. We have a record level of Current Population Survey (CPS) jobs. The non seasonally adjusted reveals this very clearly.

When the average wage is multiplied by the number of workers the monthly earnings can be calculated. The average wage is the mean wage. Some people in the press prefer the median wage, the wage above which and below which there are an equal number of wages. Some months some high wages will skew the median high while low wages may skew it lower. In order to calculate an average wage you have to multiply the number of worker, by sector, by the average weekly wage, by sector, multiply by 4 for an average monthly wage (Some months have four weeks, some have five weeks. It all works out over time.)  In order to calculate the annual wage, multiply the weekly wage by 52 and multiple that by the number of workers, do that for all sectors, and divide by the total number of workers to receive the average annual wage.

Do not be suckered by the seasonally adjusted data. The headline wage data is the seasonally adjusted average weekly wage. The number of workers in each sector is seasonally adjusted. The seasonal factors used to convert the non-seasonally adjusted (NSA) data to the seasonally adjusted (SA) data changes month to month, year to year, and sector by sector. The same is true for the seasonal factor used to convert the NSA wage to the SA wage. When you multiply seasonally adjusted workers by seasonally adjusted wages you receive seasonally adjusted garbage. Also, a three month average of an average wage can be misleading if the data doesn't sum the total wage data from each month and divide that combined number by the combined number of workers for the same period of time.  An average of an average can be misleading if the sample size is not the same, and the worker and jobs data change every month.

Unlike  most data from the government, there is not a regular "peak month" for the average hourly wage. We may be at peak weakly wage in October, November, December. We normally hit peak worker level, NSA, during July or August. We are talking average wage, so the average can increase even as gross wages (workers times monthly average) declines as workers and jobs decline.  There was a "pause" in hourly wage growth between December 2008 and September 2009. There was a similar pause between December 2009 and October 2010.

Wages are improving. Job and worker numbers are improving. Full-time jobs are replacing part-time jobs and adding additional full-time jobs. Wages times workers equals earnings. Both wages and workers are rising so earnings are growing even faster than either of the two components. Manufacturing and Construction are in recovery mode and expanding. They are not back to pre-recession levels of NSA CES workers. They are two of the highest paid sectors. As earnings improve, spending improves. As spending improves the economy improves.

It's the economy